The increasing use of wireless networks and the constant miniaturization of electrical devices has empowered the development of Wireless Body Area Networks (WBANs). In these networks various sensors are attached on clothing or on the body or even implanted under the skin. The wireless nature of the network and the wide variety of sensors offer numerous new, practical and innovative applications to improve health care and the Quality of Life. The sensors of a WBAN measure for example the heartbeat, the body temperature or record a prolonged electrocardiogram. Using a WBAN, the patient experiences a greater physical mobility and is no longer compelled to stay in the hospital. This paper offers a survey of the concept of Wireless Body Area Networks. First, we focus on some applications with special interest in patient monitoring. Then the communication in a WBAN and its positioning between the different technologies is discussed. An overview of the current research on the physical layer, existing MAC and network protocols is given. Further, cross layer and quality of service is discussed. As WBANs are placed on the human body and often transport private data, security is also considered. An overview of current and past projects is given. Finally, the open research issues and challenges are pointed out.

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A survey on wireless body area networks

Federated learning poses new statistical and systems challenges in training machine learning models over distributed networks of devices. In this work, we show that multi-task learning is naturally suited to handle the statistical challenges of this setting, and propose a novel systems-aware optimization method, MOCHA, that is robust to practical systems issues. Our method and theory for the first time consider issues of high communication cost, stragglers, and fault tolerance for distributed multi-task learning. The resulting method achieves significant speedups compared to alternatives in the federated setting, as we demonstrate through simulations on real-world federated datasets.

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Federated multi-task learning

Internet-of-Things (IoT) are everywhere in our daily life. They are used in our homes, in hospitals, deployed outside to control and report the changes in environment, prevent fires, and many more beneficial functionality. However, all those benefits can come of huge risks of privacy loss and security issues. To secure the IoT devices, many research works have been conducted to countermeasure those problems and find a better way to eliminate those risks, or at least minimize their effects on the user’s privacy and security requirements. The survey consists of four segments. The first segment will explore the most relevant limitations of IoT devices and their solutions. The second one will present the classification of IoT attacks. The next segment will focus on the mechanisms and architectures for authentication and access control. The last segment will analyze the security issues in different layers.

A Survey on Security and Privacy Issues in Internet-of-Things

Interest in Wireless Body Area Networks (WBANs) has increased significantly in recent years thanks to the advances in microelectronics and wireless communications. Owing to the very stringent application requirements in terms of reliability, energy efficiency, and low device complexity, the design of these networks requires the definition of new protocols with respect to those used in general purpose wireless sensor networks. This motivates the effort in research activities and in standardisation process of the last years. This survey paper aims at reporting an overview of WBAN main applications, technologies and standards, issues in WBANs design, and evolutions. Some case studies are reported, based on both real implementation and experimentation on the field, and on simulations. These results have the aim of providing useful insights for WBAN designers and of highlighting the main issues affecting the performance of these kind of networks.

A Survey on Wireless Body Area Networks: Technologies and Design Challenges

Ultra Wideband Signals and Systems in Communication Engineering

The Controller-Area Network (CAN) bus protocol [1] is a bus protocol invented in 1986 by Robert Bosch GmbH, originally intended for automotive use. By now, the bus can be found in devices ranging from cars and trucks, over lightning setups to industrial looms. Due to its nature, it is a system very much focused on safety, i.e., reliability. Unfortunately, there is no build-in way to enforce security, such as encryption or authentication. In this paper, we investigate the problems associated with implementing a backward compatible message authentication protocol on the CAN bus. We show which constraints such a protocol has to meet and why this eliminates, to the best of our knowledge, all the authentication protocols published so far. Furthermore, we present a message authentication protocol, CANAuth, that meets all of the requirements set forth and does not violate any constraint of the CAN bus. Keywords—CAN bus, embedded networks, broadcast authentication, symmetric cryptography

CANAuth - A Simple, Backward Compatible Broadcast Authentication Protocol for CAN bus

Authentication in conventional networks (like the Internet) is usually based upon something you know (e.g., a password), something you have (e.g., a smartcard) or something you are (biometrics). In mobile ad-hoc networks, location information can also be used to authenticate devices and users. We focus on how a provers can securely show that (s)he is within a certain distance to a verifier. Brands and Chaum proposed the distance bounding protocol as a secure solution for this problem. However, this protocol is vulnerable to a so-called "terrorist fraud attack". In this paper, we explain how to modify the distance bounding protocol to make it resistant to this kind of attacks. Recently, two other secure distance bounding protocols were published. We discuss the properties of these protocols and show how to use it as a building block in a location verification scheme

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Location verification using secure distance bounding protocols

Location information can be used to enhance mutual entity authentication protocols in wireless ad-hoc networks. More specifically, distance bounding protocols have been introduced by Brands and Chaum at Eurocrypt'93 to preclude distance fraud and mafia fraud attacks, in which a local impersonator exploits a remote honest user. Hancke and Kuhn have proposed a solution to cope with noisy channels. This paper presents an improved distance bounding protocol for noisy channels that offers a substantial reduction (about 50%) in the number of communication rounds compared to the Hancke and Kuhn protocol. The main idea is to use binary codes to correct bit errors occurring during the fast bit exchanges. Our protocol is perfectly suitable to be employed in low-cost, noisy wireless environments.

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Distance bounding in noisy environments

The emergence of pervasive computing devices has raised several privacy issues. In this paper, we address the risk of tracking attacks in RFID networks. Our contribution is threefold: (1) We repair three revised EC-RAC protocols of Lee, Batina and Verbauwhede and show that two of the improved authentication protocols are wide-strong privacy-preserving and one wide-weak privacy-preserving; (2) We present the search protocol, a novel scheme which allows for privately querying a particular tag, and proof its security properties; and (3) We design a hardware architecture to demonstrate the implementation feasibility of our proposed solutions for a passive RFID tag. Due to the specific design of our authentication protocols, they can be realized with an area significantly smaller than other RFID schemes proposed in the literature, while still achieving the required security and privacy properties.

https://cosic.esat.kuleuven.be/publications/article-1363.pdf

Low-cost untraceable authentication protocols for RFID

Physical-layer fingerprinting investigates how features extracted from radio signals can be used to uniquely identify devices. This paper proposes and analyses a novel methodology to fingerprint LoRa devices, which is inspired by recent advances in supervised machine learning and zero-shot image classification. Contrary to previous works, our methodology does not rely on localized and low-dimensional features, such as those extracted from the signal transient or preamble, but uses the entire signal. We have performed our experiments using 22 LoRa devices with 3 different chipsets. Our results show that identical chipsets can be distinguished with 59% to 99% accuracy per symbol, whereas chipsets from different vendors can be fingerprinted with 99% to 100% accuracy per symbol. The fingerprinting can be performed using only inexpensive commercial off-the-shelf software defined radios, and a low sample rate of 1 Msps. Finally, we release all datasets and code pertaining to these experiments to the public domain.

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Dave Singelée

Papers

CANAuth - A Simple, Backward Compatible Broadcast Authentication Protocol for CAN bus

Location verification using secure distance bounding protocols

Distance bounding in noisy environments

Low-cost untraceable authentication protocols for RFID

Physical-layer fingerprinting of LoRa devices using supervised and zero-shot learning